131 research outputs found

    Low Complexity Regularization of Linear Inverse Problems

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    Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of â„“2\ell^2-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

    Cross-education does not accelerate the rehabilitation of neuromuscular functions after ACL reconstruction: a randomized controlled clinical trial

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    Purpose: Cross-education reduces quadriceps weakness 8 weeks after anterior cruciate ligament (ACL) surgery, but the long-term effects are unknown. We investigated whether cross-education, as an adjuvant to the standard rehabilitation, would accelerate recovery of quadriceps strength and neuromuscular function up to 26 weeks post-surgery. Methods: Group allocation was randomized. The experimental (n = 22) and control (n = 21) group received standard rehabilitation. In addition, the experimental group strength trained the quadriceps of the non-injured leg in weeks 1–12 post-surgery (i.e., cross-education). Primary and secondary outcomes were measured in both legs 29 ± 23 days prior to surgery and at 5, 12, and 26 weeks post-surgery. Results: The primary outcome showed time and cross-education effects. Maximal quadriceps strength in the reconstructed leg decreased 35% and 12% at, respectively, 5 and 12 weeks post-surgery and improved 11% at 26 weeks post-surgery, where strength of the non-injured leg showed a gradual increase post-surgery up to 14% (all p ≤ 0.015). Limb symmetry deteriorated 9–10% more for the experimental than control group at 5 and 12 weeks post-surgery (both p ≤ 0.030). One of 34 secondary outcomes revealed a cross-education effect: Voluntary quadriceps activation of the reconstructed leg was 6% reduced for the experimental vs. control group at 12 weeks post-surgery (p = 0.023). Both legs improved force control (22–34%) and dynamic balance (6–7%) at 26 weeks post-surgery (all p ≤ 0.043). Knee joint proprioception and static balance remained unchanged. Conclusion: Standard rehabilitation improved maximal quadriceps strength, force control, and dynamic balance in both legs relative to pre-surgery but adding cross-education did not accelerate recovery following ACL reconstruction

    Competing effects of pain and fear of pain on postural control in low back pain?

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    STUDY DESIGN. A cross-sectional, observational study. OBJECTIVE. To determine whether pain and fear of pain have competing effects on postural sway in patients with low back pain (LBP). SUMMARY OF BACKGROUND DATA. Competing effects of pain and pain-related fear on postural control can be proposed as the likely explanation for inconsistent results regarding postural sway in the LBP literature. We hypothesized that although pain might increase postural sway, fear of pain might reduce sway through an increased cognitive effort or increased cocontraction to restrict body movement. The cognitive strategy would be less effective under dual-task conditions and the cocontraction strategy was expected to be less effective when standing on a narrow base of support surface. METHODS. Postural sway was measured in combined conditions of base of support (full and narrow) and cognitive loading (single and dual tasks) in 3 experimental groups with current LBP, recent LBP, and no LBP. Sway amplitude, path length, mean power frequency, and sample entropy were extracted from center-of-pressure data. RESULTS. The current-LBP group and recent-LBP group reported significantly different levels of pain, but similar levels of pain catastrophizing and kinesiophobia. The current-LBP group tended to display larger sway amplitudes in the anteroposterior direction compared with the other 2 groups. Mean power frequency values in mediolateral direction were lower in patients with the current LBP compared with recent LBP. Smaller sample entropy was found in the current-LBP group than the other groups in most experimental conditions, particularly when standing on a narrow base of support. CONCLUSION. Alterations of postural sway are mostly mediated by pain but not pain-related fear. LBP tends to increase sway amplitude, which seems to be counteracted by increased effort invested in postural control leading to decreased frequency and increased regularity of sway particularly under increased task demands. Level of Evidence: Cross-sectional study

    High fidelity computational characterization of the mechanical response of thermally aged polycarbonate

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    A representative all-atom molecular dynamics (MD) system of polycarbonate (PC) is built and conditioned to capture and predict the behaviours of PC in response to a broad range of thermo-mechanical loadings for various thermal aging. The PC system is constructed to have a distribution of molecular weights comparable to a widely used commercial PC (LEXAN 9034), and thermally conditioned to produce models for aged and unaged PC. The MD responses of these models are evaluated through comparisons to existing experimental results carried out at much lower loading rates, but done over a broad range of temperatures and loading modes. These experiments include monotonic extension/compression/shear, unilaterally and bilaterally confined compression, and load-reversal during shear. It is shown that the MD simulations show both qualitative and quantitative similarity with the experimental response. The quantitative similarity is evaluated by comparing the dilatational response under bilaterally confined compression, the shear flow viscosity and the equivalent yield stress. The consistency of the in silico response to real laboratory experiments strongly suggests that the current PC models are physically and mechanically relevant and potentially can be used to investigate thermo-mechanical response to loading conditions that would not easily be possible. These MD models may provide valuable insight into the molecular sources of certain observations, and could possibly offer new perspectives on how to develop constitutive models that are based on better understanding the response of PC under complex loadings. To this latter end, the models are used to predict the response of PC to complex loading modes that would normally be difficult to do or that include characteristics that would be difficult to measure. These include the responses of unaged and aged PC to unilaterally confined extension/compression, cyclic uniaxial/shear loadings, and sawtooth extension/compression/shear
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